Setup.
We split the COCO dataset into 20 seen (VOC) classes and 60 unseen (Non-VOC) classes. We train a model only on the annotation of 20 VOC classes and test on Non-VOC classes only. The validation split of COCO is adopted for evaluation.
Following  [1]}, we do not count the “seen class” detection boxes into the budget k when computing the Average Recall (AR@k) scores. This is to avoid evaluating any recall on seen-class objects.
